POWER SYSTEM STABILIZER TUNING TO ENHANCE KALIMANTAN SELATAN- TENGAH AND KALIMANTAN TIMUR SYSTEM INTERCONNECTION STABILITY USING PARTICLE SWARM OPTIMIZATION

• Main Author: HARTONO - NIM: 23216027 , JOKO
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/28297
• Institution: Institut Teknologi Bandung

<p align="justify">Kalimantan is one of islands in Indonesia besides Sumatera, Sulawesi, Java, and Papua. It has three subsystems that separated each other, Kalimantan Barat (Kalbar), Kalimantan Timur (Kaltim), and Kalimantan Selatan – Tengah (Kalselteng). PT PLN (Persero) as the Indonesian electicity regulator has a plan to interconnect the subsystem between Kalselteng and Kaltim to conduct the power exchange, to get realibility of the system and to get the economic values, some diesel generation whose high production cost will become the last priority to be switched on to supply the interconnection system. <br /> <br /> <br /> <br /> Based on previos study [11], the load flow of Kalselteng and Kaltim subsystems are 500 MW and 400 MW each, both of the subsystems has limited spinning reserved (10%), the spread of the load is not evenly converging in some area with long-distance transmission and there is only one generation as the base load carrier for each subsystem. One of the study result is to conduct the PSS (Power System Stabilizer) tuning in order to damp the small signal instability that appears because of those weak subsystem characteristics. This thesis exists to resolve that problem, the option that chosed is PSS tuning using PSO method. <br /> <br /> <br /> <br /> This thesis used the Kalselteng-Kaltim interconnection system model that has been develop in DIgSILENT PowerFactory®[11]. There is another software that used, MATLAB®. The first step is to determine the natural characteristics of the system especially the critical mode that shows the small signal instability, the purpose is to find the generators that associated, then tune the PSS on those generators using Particle Swarm Optimization (PSO) method in MATLAB®. After getting the tuned PSS parameter values, the system will be tested towards some small disturbance cases that compared with typical values of PSS parameter [14] to evaluate this method. <p align="justify"><br />